This research focuses on emancipative value orientations, regional factors and their interaction in determining social capital in Russia. We are especially interested in how the effects vary for formal and informal social capital, measured as different types of civic engagement. Applying multilevel regression modeling on national survey data MegaFOM 2017 and available official statistics, we find that emancipative values significantly increase the probability of taking part in civic activities, yet the effect is larger and more uniform across regions for formal social capital. Contrary to expectations and previous crosscountry studies, the moderating effect of emancipative values prevalence is either insignificant or rather unstable and goes in the negative direction. Moreover, other regional resources do not significantly moderate the relation between individual emancipative values preference and social capital.

Catalytic reforming of naphtha is one of the most important processes for high octane gasoline manufacture and aromatic hydrocarbons production. The application of computer modelling system “Catalyst's Control” for monitoring of catalytic reforming unit of Achinsk oil-refinery is stated. The mathematical model-based system takes into account the physical and chemical mechanisms of hydrocarbon mixture conversion reaction as well as the catalyst deactivation. The models created can be used for optimization and prediction of operating parameters (octane number, reactors outlet temperature and yield) of the reforming process. It is shown, that the work on the optimal activity allows increasing product output with a constant level of production costs, and get the information about Pt-Re catalyst work efficiency

The European Parliament (EP) is viewed as a normal parliament. Voting patterns of its members (MEPs) are mainly aligned with transnational political groups, not national cleavages. Yet, it has been proven by many that MEP voting patterns are an outcome of conflicting pressures and a distorted indicator of their individual political orientations. In this study we rely on MEP written questions to the European Commission to measure the policy positions and their determinants. Using the universe of 100,000+ such questions in 2002-2015 linked with MEP country and European Political Group affiliation data, we test whether one issue of high sensitivity to their domestic audiences-Russia-makes the MEPs take their nationality seriously and pay more attention to it regardless of their transnational partisan affiliations. We rely on supervised machine learning to uncover sentiment of every question asked on a negative-positive scale. Then we contrast the sentiment of questions related to Russia with the rest of questions conditional on party and national affiliation of the MEP asking the question. We find that (i) MEP question involving Russia is twice as negative in tonality as an average question, (ii) more variation in modality of Russia-related questions is explained by MEP national affiliation than her EPG. Our findings are robust to alternative methods of sentiment extraction and to controlling for time-invariant unobserved heterogeneity of MEPs. JEL Classification: F55.

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